Using Optimal Test Assembly Methods for Shortening Patient‐Reported Outcome Measures: Development and Validation of the Cochin Hand Function Scale‐6: A Scleroderma Patient‐Centered Intervention Network Cohort Study
Bibliographic record
Abstract
OBJECTIVE: To develop and validate a short form of the Cochin Hand Function Scale (CHFS), which measures hand disability, for use in systemic sclerosis, using objective criteria and reproducible techniques. METHODS: Responses on the 18-item CHFS were obtained from English-speaking patients enrolled in the Scleroderma Patient-Centered Intervention Network Cohort. CHFS unidimensionality was verified using confirmatory factor analysis, and an item response theory model was fit to CHFS items. Optimal test assembly (OTA) methods identified a maximally precise short form for each possible form length between 1 and 17 items. The final short form selected was the form with the least number of items that maintained statistically equivalent convergent validity, compared to the full-length CHFS, with the Health Assessment Questionnaire (HAQ) disability index (DI) and the physical function domain of the 29-item Patient-Reported Outcomes Measurement Information System (PROMIS-29). RESULTS: There were 601 patients included. A 6-item short form of the CHFS (CHFS-6) was selected. The CHFS-6 had a Cronbach's alpha of 0.93. Correlations of the CHFS-6 summed score with HAQ DI (r = 0.79) and PROMIS-29 physical function (r = -0.54) were statistically equivalent to the CHFS (r = 0.81 and r = -0.56). The correlation with the full CHFS was high (r = 0.98). CONCLUSION: The OTA procedure generated a valid short form of the CHFS with minimal loss of information compared to the full-length form. The OTA method used was based on objective, prespecified criteria, but should be further studied for viability as a general procedure for shortening patient-reported outcome measures in health research.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.082 | 0.161 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".